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3 commits

Author SHA1 Message Date
Simon
0cd37bdb8c Fix grouped rainfall plot views 2026-04-11 12:37:01 +01:00
Simon
b3e5998229 fix bacfill problem, add more grouping option 2026-04-11 12:30:00 +01:00
Simon
225fb1b270 add finer grouping selection 2026-04-11 12:28:42 +01:00
6 changed files with 297 additions and 52 deletions

View file

@ -365,10 +365,10 @@ empty_weather_cache <- function() {
} }
empty_metric_query <- function(aggregate = c("raw", "daily")) { empty_metric_query <- function(aggregate = c("raw", "daily", "weekly", "monthly")) {
aggregate <- match.arg(aggregate) aggregate <- match.arg(aggregate)
if (aggregate == "daily") { if (aggregate != "raw") {
return(data.frame( return(data.frame(
station_id = character(), station_id = character(),
station_name = character(), station_name = character(),
@ -820,12 +820,29 @@ get_daily_aggregate_expression <- function(metric_id) {
} }
get_time_bucket_expression <- function(aggregate = c("daily", "weekly", "monthly")) {
aggregate <- match.arg(aggregate)
switch(
aggregate,
daily = "observed_day",
weekly = paste(
"date(",
"observed_day,",
"'-' || ((CAST(strftime('%w', observed_day) AS integer) + 6) % 7) || ' days'",
")"
),
"date(observed_day, 'start of month')"
)
}
query_cached_metric <- function( query_cached_metric <- function(
location_id, location_id,
metric_id, metric_id,
start_date, start_date,
end_date = Sys.Date(), end_date = Sys.Date(),
aggregate = c("raw", "daily"), aggregate = c("raw", "daily", "weekly", "monthly"),
db_path = default_rain_db_path() db_path = default_rain_db_path()
) { ) {
aggregate <- match.arg(aggregate) aggregate <- match.arg(aggregate)
@ -840,24 +857,27 @@ query_cached_metric <- function(
start_at <- format_utc_timestamp(as.POSIXct(start_date, tz = "UTC")) start_at <- format_utc_timestamp(as.POSIXct(start_date, tz = "UTC"))
end_at <- format_utc_timestamp(as.POSIXct(end_date + 1, tz = "UTC")) end_at <- format_utc_timestamp(as.POSIXct(end_date + 1, tz = "UTC"))
sql <- if (aggregate == "daily") { sql <- if (aggregate != "raw") {
period_expression <- get_time_bucket_expression(aggregate)
sprintf( sprintf(
paste( paste(
"SELECT station_id, station_name, observed_day, metric_id, metric_label, unit,", "SELECT station_id, station_name, %s AS observed_day, metric_id, metric_label, unit,",
"%s AS value_num", "%s AS value_num",
"FROM weather_measurements", "FROM weather_measurements",
"WHERE location_id = %s", "WHERE location_id = %s",
" AND metric_id = %s", " AND metric_id = %s",
" AND observed_at >= %s", " AND observed_at >= %s",
" AND observed_at < %s", " AND observed_at < %s",
"GROUP BY station_id, station_name, observed_day, metric_id, metric_label, unit", "GROUP BY station_id, station_name, %s, metric_id, metric_label, unit",
"ORDER BY observed_day, station_name;" "ORDER BY observed_day, station_name;"
), ),
period_expression,
get_daily_aggregate_expression(metric_id), get_daily_aggregate_expression(metric_id),
sql_string(location_id), sql_string(location_id),
sql_string(metric$metric_id), sql_string(metric$metric_id),
sql_string(start_at), sql_string(start_at),
sql_string(end_at) sql_string(end_at),
period_expression
) )
} else { } else {
sprintf( sprintf(
@ -890,7 +910,7 @@ query_cached_rainfall <- function(
location_id, location_id,
start_date, start_date,
end_date = Sys.Date(), end_date = Sys.Date(),
aggregate = c("raw", "daily"), aggregate = c("raw", "daily", "weekly", "monthly"),
db_path = default_rain_db_path() db_path = default_rain_db_path()
) { ) {
aggregate <- match.arg(aggregate) aggregate <- match.arg(aggregate)
@ -997,11 +1017,13 @@ get_sync_start_date <- function(
) { ) {
metric <- get_weather_metric(metric_id) metric <- get_weather_metric(metric_id)
end_date <- as.Date(end_date) end_date <- as.Date(end_date)
requested_start_date <- end_date - as.integer(initial_backfill_days) + 1L
latest_data <- read_sqlite_query( latest_data <- read_sqlite_query(
sprintf( sprintf(
paste( paste(
"SELECT MAX(observed_at) AS latest_observed_at", "SELECT MIN(observed_at) AS earliest_observed_at,",
"MAX(observed_at) AS latest_observed_at",
"FROM weather_measurements", "FROM weather_measurements",
"WHERE location_id = %s", "WHERE location_id = %s",
" AND metric_id = %s;" " AND metric_id = %s;"
@ -1012,12 +1034,22 @@ get_sync_start_date <- function(
db_path = db_path db_path = db_path
) )
earliest_observed_at <- if (nrow(latest_data)) latest_data$earliest_observed_at[1] else ""
latest_observed_at <- if (nrow(latest_data)) latest_data$latest_observed_at[1] else "" latest_observed_at <- if (nrow(latest_data)) latest_data$latest_observed_at[1] else ""
if (is.na(latest_observed_at) || !nzchar(latest_observed_at)) { if (is.na(latest_observed_at) || !nzchar(latest_observed_at)) {
return(end_date - as.integer(initial_backfill_days) + 1L) return(requested_start_date)
} }
as.Date(latest_observed_at, format = "%Y-%m-%dT%H:%M:%SZ") - as.integer(overlap_days) earliest_observed_day <- as.Date(earliest_observed_at, format = "%Y-%m-%dT%H:%M:%SZ")
latest_observed_day <- as.Date(latest_observed_at, format = "%Y-%m-%dT%H:%M:%SZ")
if (!is.na(earliest_observed_day) && earliest_observed_day > requested_start_date) {
return(requested_start_date)
}
if (latest_observed_day > end_date) {
return(end_date + 1L)
}
latest_observed_day - as.integer(overlap_days)
} }
@ -1148,7 +1180,7 @@ sync_location_rainfall <- function(
if (start_date > end_date) { if (start_date > end_date) {
return(data.frame( return(data.frame(
location_id = location_id, location_id = location_id,
start_date = as.character(start_date), start_date = "",
end_date = as.character(end_date), end_date = as.character(end_date),
rows_fetched = 0L, rows_fetched = 0L,
rows_written = 0L, rows_written = 0L,
@ -1410,7 +1442,7 @@ compute_plot_limits <- function(values) {
plot_cached_metric <- function( plot_cached_metric <- function(
metric_data, metric_data,
metric_id, metric_id,
view = c("raw", "daily"), view = c("raw", "daily", "weekly", "monthly"),
main = NULL main = NULL
) { ) {
view <- match.arg(view) view <- match.arg(view)
@ -1427,7 +1459,7 @@ plot_cached_metric <- function(
y_limits <- compute_plot_limits(metric_data$value_num) y_limits <- compute_plot_limits(metric_data$value_num)
y_label <- sprintf("%s (%s)", metric$label, metric$unit) y_label <- sprintf("%s (%s)", metric$label, metric$unit)
if (view == "daily") { if (view != "raw") {
metric_data$observed_day <- as.Date(metric_data$observed_day) metric_data$observed_day <- as.Date(metric_data$observed_day)
plot( plot(
@ -1493,7 +1525,7 @@ plot_cached_metric <- function(
plot_cached_rainfall <- function( plot_cached_rainfall <- function(
rain_data, rain_data,
view = c("raw", "daily"), view = c("raw", "daily", "weekly", "monthly"),
hide_zero = TRUE, hide_zero = TRUE,
main = NULL main = NULL
) { ) {

140
app.R
View file

@ -84,6 +84,99 @@ format_window_label <- function(amount, unit) {
sprintf("last %s %s", amount, unit_label) sprintf("last %s %s", amount, unit_label)
} }
get_rain_view_choices <- function(window_unit = "days") {
switch(
window_unit,
days = c(
"6-minute rain" = "raw",
"Daily total" = "daily"
),
months = c(
"Daily total" = "daily",
"Weekly total" = "weekly"
),
years = c(
"Weekly total" = "weekly",
"Monthly total" = "monthly"
),
c(
"6-minute rain" = "raw",
"Daily total" = "daily"
)
)
}
get_metric_view_choices <- function(window_unit = "days") {
switch(
window_unit,
days = c(
"Raw observations" = "raw",
"Daily aggregate" = "daily"
),
months = c(
"Daily aggregate" = "daily",
"Weekly aggregate" = "weekly"
),
years = c(
"Weekly aggregate" = "weekly",
"Monthly aggregate" = "monthly"
),
c(
"Raw observations" = "raw",
"Daily aggregate" = "daily"
)
)
}
get_preferred_window_view <- function(window_unit = "days") {
switch(
window_unit,
days = "raw",
months = "weekly",
years = "monthly",
"raw"
)
}
get_summary_aggregate <- function(window_unit = "days") {
switch(
window_unit,
days = "daily",
months = "weekly",
years = "monthly",
"daily"
)
}
format_aggregate_label <- function(aggregate = c("raw", "daily", "weekly", "monthly")) {
aggregate <- match.arg(aggregate)
switch(
aggregate,
raw = "Raw",
daily = "Daily",
weekly = "Weekly",
monthly = "Monthly"
)
}
format_aggregate_period_label <- function(aggregate = c("daily", "weekly", "monthly")) {
aggregate <- match.arg(aggregate)
switch(
aggregate,
daily = "Day",
weekly = "Week",
monthly = "Month"
)
}
ui <- fluidPage( ui <- fluidPage(
tags$head( tags$head(
tags$style(HTML(" tags$style(HTML("
@ -188,7 +281,7 @@ ui <- fluidPage(
class = "panel-card", class = "panel-card",
h3(class = "panel-title", "Rain"), h3(class = "panel-title", "Rain"),
withSpinner(plotOutput("rainPlot", height = "420px")), withSpinner(plotOutput("rainPlot", height = "420px")),
h4("Daily rain totals"), h4(textOutput("summaryTitle", container = span)),
tableOutput("dailySummary") tableOutput("dailySummary")
) )
), ),
@ -223,11 +316,24 @@ server <- function(input, output, session) {
observeEvent(input$window_unit, { observeEvent(input$window_unit, {
settings <- get_window_slider_config(input$window_unit) settings <- get_window_slider_config(input$window_unit)
preferred_view <- get_preferred_window_view(input$window_unit)
rain_choices <- get_rain_view_choices(input$window_unit)
metric_choices <- get_metric_view_choices(input$window_unit)
current_value <- if (is.null(input$window_amount)) { current_value <- if (is.null(input$window_amount)) {
settings$value settings$value
} else { } else {
as.integer(input$window_amount) as.integer(input$window_amount)
} }
current_rain_view <- if (!is.null(input$rain_view_mode) && input$rain_view_mode %in% rain_choices) {
input$rain_view_mode
} else {
preferred_view
}
current_metric_view <- if (!is.null(input$metric_view_mode) && input$metric_view_mode %in% metric_choices) {
input$metric_view_mode
} else {
preferred_view
}
updateSliderInput( updateSliderInput(
session = session, session = session,
@ -238,6 +344,20 @@ server <- function(input, output, session) {
value = min(max(current_value, 1L), settings$max), value = min(max(current_value, 1L), settings$max),
step = 1 step = 1
) )
updateRadioButtons(
session = session,
inputId = "rain_view_mode",
choices = rain_choices,
selected = current_rain_view
)
updateRadioButtons(
session = session,
inputId = "metric_view_mode",
choices = metric_choices,
selected = current_metric_view
)
}, ignoreInit = TRUE) }, ignoreInit = TRUE)
selected_start_date <- reactive({ selected_start_date <- reactive({
@ -259,6 +379,10 @@ server <- function(input, output, session) {
as.integer(Sys.Date() - selected_start_date()) + 1L as.integer(Sys.Date() - selected_start_date()) + 1L
}) })
selected_summary_aggregate <- reactive({
get_summary_aggregate(input$window_unit)
})
cached_rain <- reactive({ cached_rain <- reactive({
data_version() data_version()
@ -291,7 +415,7 @@ server <- function(input, output, session) {
location_id = input$location_id, location_id = input$location_id,
start_date = selected_start_date(), start_date = selected_start_date(),
end_date = Sys.Date(), end_date = Sys.Date(),
aggregate = "daily", aggregate = selected_summary_aggregate(),
db_path = db_path db_path = db_path
) )
}) })
@ -310,6 +434,13 @@ server <- function(input, output, session) {
selected_metric()$label selected_metric()$label
}) })
output$summaryTitle <- renderText({
sprintf(
"%s rain totals",
format_aggregate_label(selected_summary_aggregate())
)
})
output$syncControls <- renderUI({ output$syncControls <- renderUI({
if (is.null(api_headers)) { if (is.null(api_headers)) {
return( return(
@ -474,8 +605,9 @@ server <- function(input, output, session) {
return(NULL) return(NULL)
} }
names(summary_data) <- c("Station ID", "Station", "Day", "Metric", "Label", "Unit", "Rain") period_label <- format_aggregate_period_label(selected_summary_aggregate())
summary_data[, c("Station", "Day", "Rain")] names(summary_data) <- c("Station ID", "Station", period_label, "Metric", "Label", "Unit", "Rain")
summary_data[, c("Station", period_label, "Rain")]
}, striped = TRUE, spacing = "s", digits = 2) }, striped = TRUE, spacing = "s", digits = 2)
output$metricLatest <- renderTable({ output$metricLatest <- renderTable({

View file

@ -9,40 +9,32 @@ headers.default <- add_headers(
apikey = token4 apikey = token4
) )
getAllFromCoord <- function(coord,start_date,end_date,allstations,N=3,headers,base="https://public-api.meteofrance.fr"){
three_station=getIdFromCoords(coord,allstations,N=N)
alldata=lapply(three_station$Id_station,function(statid){
print(paste("recuperer station",statid))
allstat=tryCatch(getStationData(start_date=start_date,end_date=end_date,station_id=statid,headers=headers,base=base),
error=function(e){print(e);NULL})
print(paste("done, sleep 5 sec"))
print(dim(allstat))
Sys.sleep(5)
return(allstat)
})
alldata= do.call("rbind.data.frame",alldata)
ids=three_station$Nom_usuel
names(ids)=three_station$Id_station
cbind.data.frame(alldata,Nom_usuel=ids[as.character(alldata[,1])])
}
allstations=read.csv("allstations.csv") #get all station allstations=read.csv("allstations.csv") #get all station
lacouch.coor <- c(45.3722971,5.6387118) lacouch.coor <- c(45.3722971,5.6387118)
lamure.coor <- c(44.9167, 5.8000)
vignass.coor=c(44.8550665,5.8441789) vignass.coor=c(44.8550665,5.8441789)
foreve=list() foreve=list()
for(y in 0:3){ n_periods = 10
enddate=format(Sys.Date()-y*365, "%Y-%m-%d") for (i in 0:(n_periods-1)) {
startdate=format(Sys.Date()-(y*365+364), "%Y-%m-%d") enddate = format(Sys.Date() - i * 182, "%Y-%m-%d") # Approximately 6 months, adjust if you need more precision
foreve=tryCatch(getAllFromCoord(vignass.coor,startdate,enddate,allstations,headers=headers.default,base="https://public-api.meteofrance.fr"),error=function(e)e) # Calculate start date for the period, 182 days before the end date
startdate = format(Sys.Date() - (i * 182 + 181), "%Y-%m-%d") # Approximately 6 months
foreve[[paste0("per",i)]]=tryCatch(getAllFromCoord(lacouch.coor,startdate,enddate,allstations,headers=headers.default,base="https://public-api.meteofrance.fr"),error=function(e)e)
} }
test1=getAllFromCoord(vignass.coor,start_date=startdate,end_date=enddate,allstations,headers=headers.default) startdate = format(Sys.Date() - 5, "%Y-%m-%d")
test1=getAllFromCoord(vignass.coor,start_date=startdate,end_date= format(Sys.Date() , "%Y-%m-%d"),allstations,headers=headers.default)
#test1=do.call("rbind.data.frame",foreve)
#test1=read.csv("allvignass.csv")[,-1]
cols=palette.colors()[1:length(unique(test1$Nom_usuel))] cols=palette.colors()[1:length(unique(test1$Nom_usuel))]
names(cols)=unique(test1$Nom_usuel) names(cols)=unique(test1$Nom_usuel)
plot(getDate(test1[,2]),test1[,3],pch=20,col=cols[test1$Nom_usuel],cex=2) testsep=test1#[test1[,3]>0,]
testsep[testsep[,3]==0,c(3,4)]=NA
testsep=testsep[getDate(testsep[,2])>a,]
plot(getDate(testsep[,2]),testsep[,3],pch=20,col=adjustcolor(cols[testsep$Nom_usuel],.4),cex=1.3,ylim=c(0,8))
legend("topleft",col=cols,legend=names(cols),pch=20,cex=2) legend("topleft",col=cols,legend=names(cols),pch=20,cex=2)
abline(v=as.numeric(as.POSIXlt("2024-08-07",format="%Y-%m-%d")),lwd=3,col="red") abline(v=as.numeric(as.POSIXlt("2024-08-07",format="%Y-%m-%d")),lwd=3,col="red")
#write.csv(file="allvignass.csv",test1)

View file

@ -8,6 +8,10 @@ headersLIM <- add_headers(
accept = "*/*", accept = "*/*",
apikey = token2 apikey = token2
) )
headersLIM2 <- add_headers(
accept = "*/*",
apikey = token
)
headersPaquet <- add_headers( headersPaquet <- add_headers(
accept = "*/*", accept = "*/*",
apikey = yearTokenPaquer apikey = yearTokenPaquer
@ -21,19 +25,55 @@ start_date <- as.Date("2024-03-24")
end_date <- as.Date("2024-08-14") end_date <- as.Date("2024-08-14")
station_id <- "38269004" station_id <- "38269004"
allstations=getStations(headersLIM) #allstations=getStations(headersLIM)
allstations=read.csv("allstations.csv") allstations=read.csv("allstations.csv")
#write.csv(file="allstations.csv",allstation,row.names=F) #write.csv(file="allstations.csv",allstation,row.names=F)
lacouch=c(45.3722971,5.6387118) lacouch.coor <- c(45.3722971,5.6387118)
lamure.coor <- c(44.9167, 5.8000)
alldist=dist(rbind(lacouch,cbind(allstations$Latitude,allstations$Longitude))) vignass.coor=c(44.8550665,5.8441789)
staupre=allstation$Id_station[which.min(as.matrix(alldist)[1,-1])]
lamure=38269004
allmure=getStationData(start_date="2024-06-24",end_date="2024-08-14",station_id=lamure,headers=headersLIM) lamure.id=38269004
lavaldens.id=38269004
lacouch.id=38269004
lacouch.stats=getIdFromCoords(lacouch.coor,allstations,N=3)
lamure.stats=getIdFromCoords(lamure.coor,allstations,N=3)
vignass.stats=getIdFromCoords(vignass.coor,allstations,N=3)
allvignass=getStationData(start_date="2024-06-24",end_date="2024-08-14",station_id=lamure.id,headers=headersLIM)
alllavaldens=getStationData(start_date="2024-06-24",end_date="2024-08-14",station_id=38207001,headers=headersLIM) alllavaldens=getStationData(start_date="2024-06-24",end_date="2024-08-14",station_id=38207001,headers=headersLIM)
allcouch=getStationData(start_date="2024-06-24",end_date="2024-08-16",station_id=lacouch.id,headers=headersLIM)
today=format(Sys.Date(), "%Y-%m-%d")
monthan=format(Sys.Date()-45, "%Y-%m-%d")
allvignass=lapply(vignass.stats$Id_station,function(statid){print(paste("recuperer station",statid));Sys.sleep(5);getStationData(start_date=monthan,end_date=today,station_id=statid,headers=headersLIM);paste("done, sleep 5 sec");Sys.sleep(5)})
alllacouch=lapply(lacouch.stats$Id_station,function(statid){print(paste("recuperer station",statid));statdat=tryCatch(getStationData(start_date=monthan,end_date=today,station_id=statid,headers=headersLIM),error=function(e)NULL);paste("done, sleep 5 sec");Sys.sleep(5);statdat})
getStationData(start_date="2024-07-04",end_date="2024-08-16",station_id=vignass.stats$Id_station[3],headers=headersLIM)
allvignass.df=do.call("rbind.data.frame",allvignass)
allvignass.df=allvignass.df[allvignass.df[,3]>0,]
ids=vignass.stats$Nom_usuel
names(ids)=vignass.stats$Id_station
cols=palette.colors()[1:nrow(vignass.stats)]
names(cols)=vignass.stats$Id_station
plot(getDate(allvignass.df[,2]),allvignass.df[,3],pch=20,col=cols[as.character(allvignass.df[,1])],cex=2)
legend("topleft",col=cols,legend=ids[names(cols)],pch=20,cex=2)
abline(v=as.numeric(as.POSIXlt("2024-08-07",format="%Y-%m-%d")),lwd=3,col="red")
alllacouch=do.call("rbind.data.frame",alllacouch)
alllacouch=alllacouch[alllacouch[,3]>0,]
ids=lacouch.stats$Nom_usuel
names(ids)=lacouch.stats$Id_station
cols=palette.colors()[1:nrow(lacouch.stats)]
names(cols)=lacouch.stats$Id_station
plot(getDate(alllacouch[,2]),alllacouch[,3],pch=20,col=cols[as.character(alllacouch[,1])],cex=2)
legend("topleft",col=cols,legend=ids[names(cols)],pch=20,cex=2)
paquetLamure=getStationPaquet(id_station=lamure) paquetLamure=getStationPaquet(id_station=lamure)
allcouch=getStationData(start_date="2024-06-24",end_date="2024-08-14",station_id=staupre,headers=headersLIM)
allal=getStationData(start_date="2024-01-24",end_date="2024-08-13",station_id=staupre,headers=headersLIM) allal=getStationData(start_date="2024-01-24",end_date="2024-08-13",station_id=staupre,headers=headersLIM)
plot(getDate(alllavaldens[,2]),alllavaldens[,3],lwd=3,type="l",col="red") plot(getDate(alllavaldens[,2]),alllavaldens[,3],lwd=3,type="l",col="red")

View file

@ -158,7 +158,7 @@ for (location_index in seq_along(location_ids)) {
status <- get_location_cache_status(location_id, db_path = db_path) status <- get_location_cache_status(location_id, db_path = db_path)
results[[location_index]] <- data.frame( results[[location_index]] <- data.frame(
location_id = location_id, location_id = location_id,
start_date = as.character(location_start_date), start_date = "",
end_date = as.character(end_date), end_date = as.character(end_date),
chunk_days = chunk_days, chunk_days = chunk_days,
rows_fetched = 0L, rows_fetched = 0L,

View file

@ -162,7 +162,11 @@ test_that("SQLite cache upserts and queries multiple metrics from one dataset",
expect_equal(latest_temperature$value_num[1], 22) expect_equal(latest_temperature$value_num[1], 22)
expect_equal( expect_equal(
as.character(get_sync_start_date("vignasses", db_path, end_date = as.Date("2024-01-10"))), as.character(get_sync_start_date("vignasses", db_path, end_date = as.Date("2024-01-10"))),
"2024-01-01" "2023-12-21"
)
expect_equal(
as.character(get_sync_start_date("vignasses", db_path, end_date = as.Date("2024-01-01"))),
"2023-12-12"
) )
}) })
@ -178,3 +182,48 @@ test_that("sync ranges are chunked predictably", {
expect_equal(as.character(ranges$start_date[1]), "2024-01-01") expect_equal(as.character(ranges$start_date[1]), "2024-01-01")
expect_equal(as.character(ranges$end_date[3]), "2024-05-15") expect_equal(as.character(ranges$end_date[3]), "2024-05-15")
}) })
test_that("weekly and monthly rainfall aggregates collapse long windows", {
skip_if_not(nzchar(Sys.which("sqlite3")), "sqlite3 is required for cache tests.")
db_path <- tempfile(fileext = ".sqlite")
on.exit(unlink(c(db_path, paste0(db_path, c("-shm", "-wal")))), add = TRUE)
ensure_weather_db(db_path)
rain_rows <- normalise_rainfall_data(
raw_data = data.frame(
POSTE = c("1001", "1001", "1001"),
DATE = c(202401020000, 202401090000, 202402010000),
RR6 = c(1, 2, 3),
Nom_usuel = c("Station A", "Station A", "Station A"),
stringsAsFactors = FALSE
),
location_id = "vignasses",
fetched_at = as.POSIXct("2026-04-08 09:00:00", tz = "UTC")
)
expect_equal(upsert_weather_measurements(rain_rows, db_path), 3)
weekly_rain <- query_cached_rainfall(
location_id = "vignasses",
start_date = "2024-01-01",
end_date = "2024-02-01",
aggregate = "weekly",
db_path = db_path
)
monthly_rain <- query_cached_rainfall(
location_id = "vignasses",
start_date = "2024-01-01",
end_date = "2024-02-01",
aggregate = "monthly",
db_path = db_path
)
expect_equal(as.character(weekly_rain$observed_day), c("2024-01-01", "2024-01-08", "2024-01-29"))
expect_equal(weekly_rain$rain_mm, c(1, 2, 3))
expect_equal(as.character(monthly_rain$observed_day), c("2024-01-01", "2024-02-01"))
expect_equal(monthly_rain$rain_mm, c(3, 3))
})